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Mining Industrial Engineered Data of Apparel Industry: A Proposed Methodology

by Md Shamsur Rahim, Mashiour Rahman, Azm Ehtesham Chowdhury
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 161 - Number 7
Year of Publication: 2017
Authors: Md Shamsur Rahim, Mashiour Rahman, Azm Ehtesham Chowdhury
10.5120/ijca2017913262

Md Shamsur Rahim, Mashiour Rahman, Azm Ehtesham Chowdhury . Mining Industrial Engineered Data of Apparel Industry: A Proposed Methodology. International Journal of Computer Applications. 161, 7 ( Mar 2017), 1-7. DOI=10.5120/ijca2017913262

@article{ 10.5120/ijca2017913262,
author = { Md Shamsur Rahim, Mashiour Rahman, Azm Ehtesham Chowdhury },
title = { Mining Industrial Engineered Data of Apparel Industry: A Proposed Methodology },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 161 },
number = { 7 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume161/number7/27157-2017913262/ },
doi = { 10.5120/ijca2017913262 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:06:28.372705+05:30
%A Md Shamsur Rahim
%A Mashiour Rahman
%A Azm Ehtesham Chowdhury
%T Mining Industrial Engineered Data of Apparel Industry: A Proposed Methodology
%J International Journal of Computer Applications
%@ 0975-8887
%V 161
%N 7
%P 1-7
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining and knowledge discovery play a significant role in the field of industrial engineering as the vast amount of generated data help to reveal previously unknown interesting patterns and knowledge. Many industries have already adopted data mining techniques for better productivity by following clear and concise methodologies. But apparel industries are yet waiting to adopt data mining techniques due to the absence of a data mining methodology which meets the particular requirements and business objectives. The objective of this research is to develop such a mining methodology that will be able to fulfill the requirements of apparel industries. This research paper has proposed a methodology for mining industrial engineered manufacturing data of apparel industries. This methodology covers from analysis of apparel industrys manufacturing unit to implement and evaluate mining model. It also includes the analysis of different departments in manufacturing to identify correlation and dependencies among the departments which is absent in the existing methodologies. Furthermore, the proposed methodology provides a clear and unambiguous transitions among different steps to perform data mining.

References
  1. Jiawei Han, Jian Pei, and Micheline Kamber. Data mining: concepts and techniques. Elsevier, 2011.
  2. Chih-Hung Hsu. Data mining to improve industrial standards and enhance production and marketing: An empirical study in apparel industry. Expert Systems with Applications, 36(3):4185–4191, 2009.
  3. Naresh Paneru et al. Implementation of lean manufacturing tools in garment manufacturing process focusing sewing section of mens shirt. 2011.
  4. Jose Solarte. A proposed data mining methodology and its application to industrial engineering. 2002.
  5. Melissa Breyer. 25 shocking fashion industry statistics, Sep 2012.
  6. Malcolm Newbery. Apparel manufacturing technology. Aroq Limited, 2005.
  7. Christoph Gr¨oger, Florian Niedermann, and Bernhard Mitschang. Data mining-driven manufacturing process optimization. In Proceedings of the world congress on engineering, volume 3, pages 4–6, 2012.
  8. Bangladesh is second-largest global apparel exporter - retailers’ hub: India’s ’dollar city’ tirupur on a rise, but bangladesh reigns supreme, Jul 2013.
  9. Flow chart of garments manufacturing process, Jul 2015.
  10. Martand Telsang. Industrial engineering and production management. S. Chand, 2006.
  11. Prasanta Sarkar. Duties and responsibilities of industrial engineering department.
  12. Sewon Oh, Jooyung Han, and Hyunbo Cho. Intelligent process control system for quality improvement by data mining in the process industry. In Data mining for design and manufacturing, pages 289–309. Springer, 2001.
  13. Victor A Skormin, Vladimir I Gorodetski, and Leonard J Popyack. Data mining technology for failure prognostic of avionics. IEEE Transactions on Aerospace and Electronic Systems, 38(2):388–403, 2002.
  14. Wei-Chou Chen, Shian-Shyong Tseng, and Ching-YaoWang. A novel manufacturing defect detection method using association rule mining techniques. Expert systems with applications, 29(4):807–815, 2005.
  15. Lixiang Shen, Francis EH Tay, Liangsheng Qu, and Yudi Shen. Fault diagnosis using rough sets theory. Computers in industry, 43(1):61–72, 2000.
  16. Dentcho Batanov, Nagen Nagarur, and Prapan Nitikhunkasem. Expert-mm: A knowledge-based system for maintenance management. Artificial intelligence in engineering, 8(4):283–291, 1993.
  17. Carol J Romanowski and Rakesh Nagi. Analyzing maintenance data using data mining methods. In Data mining for design and manufacturing, pages 235–254. Springer, 2001.
  18. Reimund Belz and Peter Mertens. Combining knowledgebased systems and simulation to solve rescheduling problems. Decision Support Systems, 17(2):141–157, 1996.
  19. JA Srinivas and Muhammad Shahbaz. Agent oriented planning using data mined knowledge. In 10th International Conference on Concurrent Engineering, Adaptive Engineering for Sustainable Value Creation, pages 301–307, 2004.
  20. Gregory Piatetsky. Kdnuggets, Oct 2014.
  21. Ana Isabel Roj˜ao Lourenc¸o Azevedo and Manuel Filipe Santos. Kdd, semma crisp-dm: a parallel overviee. IADS-DM, 2008.
  22. Pete Chapman, Julian Clinton, Randy Kerber, Thomas Khabaza, Thomas Reinartz, Colin Shearer, and Rudiger Wirth. Crisp-dm 1.0 step-by-step data mining guide. 2000.
  23. Seyyed Soroush Rohanizadeh and Mohammad Bameni Moghadam. A proposed data mining methodology and its application to industrial procedures. Journal of Industrial Engineering, 4(1):37–50, 2009.
  24. John B. Rollins. Foundational methodology for data science. 2015.
  25. Mining models (analysis services - data mining).
Index Terms

Computer Science
Information Sciences

Keywords

Apparel industry industrial engineering data mining data mining methodology manufacturing data